Dynamic Reporting

Overview

1. What is dynamic reporting?

2. How to do dynamic reporting?

3. Hands-on exercises

Manual reporting workflow

What are the disadvantages?

Dynamic reporting workflow

Popular tools for dynamic reporting

Which tool for whom?

• knitr → R+LaTeX users (intermediate to advanced)
• R Markdown → R users (beginner to advanced)
• Quarto → R/Python/Julia users (beginner to advanced)

Useful links 1

• Dynamic Reporting & Reproducibility in Research
  → transdisciplinary course at UZH

• Dynamic Reporting Primer
  → Primer article from the CRS

• R Markdown tutorial
  → good tutorial series from R Studio

• R Markdown: The Definitive Guide
  → freely available book

Useful links 2

• knitr website
  → very comprehensive website from the knitr author

• Quarto tutorial
  → good tutorial series from R Studio

• R Markdown cheatsheet

Exercises

1. Download the data sets on traffic accidents in Zurich from https://github.crsuzh/dynamicReporting/workshop/.

2. Explore the data from the 2020 (file accidents_2020.csv) . Compute the number of accidents for each weekday and month. Make plots of the number of accidents vs. weekday, and the number of accidents vs. month. Create an HTML report using either R Markdown or Quarto.

3. Now use the data from 2020 and 2021 (file accidents_2021.csv) and create an updated report.

4. Bonus: Convert your report to a presentation.

Backup: R Markdown

• R programming language
  (> 60 other also possible)

• .Rmd files (edit in RStudio, VS Code, etc.)

• Markup language: Markdown

• HTML, PDF, DOCX output formats (and more)

• rmarkdown is an R package

Backup: knitr

• Programming language: R
  (> 60 other also possible)

• .Rnw files (edit in RStudio, VS Code, etc.)

• Markup languages: LaTeX
  (+ HTML, Markdown, and more)

• PDF output format (and more)

• knitr is an R package

Backup: Quarto

• Programming language: R, Python, Julia

• .qmd files (edit in RStudio, VS Code, etc.)

• Markup language: Markdown

• HTML, PDF, DOCX output formats (and more)

• Evolution of R Markdown (introduced in 2022)

• quarto is a separate program

Backup: Code in Quarto Presentation

print("Hello quarto")

[1] "Hello quarto"

x <- seq(-3, 3, 0.01)
plot(x, dnorm(x), type = "l")